Detection and Isolation of Pectoral Muscle from Digital Mammogram: An Automated Approach

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Indra Kanta Maitra
Sanjay Nag, Samir K. Bandyopadhyay


Computer Aided Diagnosis (CAD) systems have improved diagnosis of abnormalities in mammogram images. Extraction of the breast
region allows the search for abnormalities to be limited to the region of the breast without undue influence from the non-breast region. After
performing essential pre-processing steps the exact breast region as the region of interest (ROI), has to be segmented. In this paper we propose a
fully automated detection, isolation and segmentation of Pectoral Muscle from the breast region in mammographic images. This composite
method have been implemented and applied to MIAS mammographic database using ground truth images and quantitative metrics to evaluate its
performance characteristics.



Keywords: Mammogram, Gaussian Smoothening; Binary Homogeneity Enhancement Algorithm (BHEA); Edge Detection Algorithm (EDA);
Pectoral Muscle Detection Algorithm (PMDA); Pectoral Boundary Smoothening Algorithm (PBSA).


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